Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-25T05:53:36.043Z Has data issue: false hasContentIssue false
  • English
  • Français

Virtual decomposition control of an exoskeleton robot arm

Published online by Cambridge University Press:  15 October 2014

Cristóbal Ochoa Luna ,
Mohammad Habibur Rahman ,
Maarouf Saad ,
Philippe Archambault  and
Wen-Hong Zhu
Cristóbal Ochoa Luna*
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Montreal, Canada. Emails: [email protected], [email protected]
Mohammad Habibur Rahman
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Montreal, Canada. Emails: [email protected], [email protected] School of Physical & Occupational Therapy, McGill University, Montreal, Quebec, Canada. Email: [email protected]
Maarouf Saad
Affiliation:
Department of Electrical Engineering, École de technologie supérieure, Montreal, Canada. Emails: [email protected], [email protected]
Philippe Archambault
Affiliation:
School of Physical & Occupational Therapy, McGill University, Montreal, Quebec, Canada. Email: [email protected] Center for Interdisciplinary Research in Rehabilitation (CRIR), Montreal, Quebec, Canada
Wen-Hong Zhu
Affiliation:
Space Exploration, Canadian Space Agency, Longueuil, Quebec, Canada. Email: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach.

Keywords

Exoskeleton robotVirtual decomposition controlPassive rehabilitationActive rehabilitationUpper-limb impairmentDynamic variations
Type
Articles
Information
Robotica , Volume 34 , Issue 7 , July 2016 , pp. 1587 - 1609
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Pons, J. L., Wearable Robots: Biomechatronic Exoskeletons (Wiley, Hoboken, N. J., 2008).Google Scholar
2.United Nations, Department of Economic and Social Affairs, Population Division, World Population Ageing 2013 (United Nations, New York, 2013).Google Scholar
3.Mackay, J. and Mensah, G. A., The Atlas of Heart Disease and Stroke, (World Health Organization, Geneva, Switzerland, 2004) pp. 50–53.Google Scholar
4.Garrec, P., Friconneau, J. P., Measson, Y. and Perrot, Y., “ABLE, an Innovative Transparent Exoskeleton for the Upper-Limb,” IEEE/RSJ International Conference on Intelligent Robots and Systems, (2008) pp. 1483–1488.Google Scholar
5.Nef, T., Guidali, M., Klamroth-Marganska, V. and Riener, R., “ARMin - Exoskeleton Robot for Stroke Rehabilitation,” World Congress on Medical Physics and Biomedical Engineering, Munich, Germany (September 7–12, 2009), (Dössel, O. and Schlegel, W., eds.) (Springer Berlin Heidelberg, 2009), pp. 127–130.Google Scholar
6.Rahman, M. H., Saad, M., Kenné, J. P., Archambault, P. S. and Ouimet, T. K., “Development of a 4DoFs exoskeleton robot for passive arm movement assistance,” Int. J. Mechatronics Autom. 2 (1), 34–50 (2012).Google Scholar
7.Van der Loos, H. M. and Reinkensmeyer, D. J., “Rehabilitation and Health Care Robotics” In: Springer Handbook of Robotics (Siciliano, B. and Khatib, O., eds.), (Springer, Berlin Heidelberg, 2008) pp. 1225–1227.Google Scholar
8.Perry, J. C. and Rosen, J., “Design of a 7 Degree-of-Freedom Upper-Limb Powered Exoskeleton,” The First IEEE/RAS-EMBS International Conference on, Biomedical Robotics and Biomechatronics, 2006. BioRob 2006. (2006) pp. 805–810.Google Scholar
9.Tsagarakis, N., Caldwell, D. G. and Medrano-Cerda, G. A., “A 7 DOF Pneumatic Muscle Actuator (pMA) Powered Exoskeleton,” 8th IEEE International Workshop on, Robot and Human Interaction, 1999. (1999) pp. 327–333.Google Scholar
10.Norouzi-Gheidari, N., Archambault, P. S. and Fung, J., “Effects of robot-assisted therapy on stroke rehabilitation in upper limbs: Systematic review and meta-analysis of the literature,” J. Rehabil. Res. Dev. 49 (4), 479–496 (2012).Google Scholar
11.Sarakoglou, I., Kousidou, S., Tsagarakis, N. G. and Caldwell, D. G., “Exoskeleton-based exercisers for the disabilities of the upper arm and hand” In: Rehabilitation Robotics (Kommu, S. S., ed.) (I-Tech Education and Publishing, 2007) pp. 499–522.Google Scholar
12.Lo, H. S. and Xie, S. Q., “Exoskeleton robots for upper-limb rehabilitation: State of the art and future prospects,” Med. Eng. Phys. 34 (3), 261–268 (2012).Google Scholar
13.Eschweiler, J., Gerlach-Hahn, K., Jansen-Toy, A. and Leonhardt, S., “A survey on robotic devices for upper limb rehabilitation,” J. Neuroengineering Rehabil. 11 (1), 3 (2014).Google Scholar
14.Rahman, M. H., Rahman, M. J., Cristobal, O. L., Saad, M., Kenné, J. P. and Archambault, P. S., “Development of a whole arm wearable robotic exoskeleton for rehabilitation and to assist upper limb movements,” Robotica, Available on CJO 2014 doi:10.1017/S0263574714000034.Google Scholar
15.Sun, F. C., Sun, Z. Q. and Feng, G., “An adaptive fuzzy controller based on sliding mode for robot manipulators,” IEEE Trans. Syst. Man Cybern. B 29 (5), 661–667 (1999).Google Scholar
16.Uzmay, I. and Burkan, R., “Parameter estimation and upper bounding adaptation in adaptive-robust control approaches for trajectory control of robots,” Robotica 20 (06), 653–660 (2002).CrossRefGoogle Scholar
17.Song, Z., Yi, J., Zhao, D. and Li, X., “A computed torque controller for uncertain robotic manipulator systems: Fuzzy approach,” Fuzzy Sets Syst. 154 (2), 208–226 (2005).CrossRefGoogle Scholar
18.Ciliz, M. K., “Adaptive control of robot manipulators with neural network based compensation of frictional uncertainties,” Robotica 23 (02), 159–167 (2005).Google Scholar
19.Li, Z., Ge, S. S., Adams, M. and Wijesoma, W. S., “Robust adaptive control of uncertain force/motion constrained nonholonomic mobile manipulators,” Automatica 44 (3), 776–784 (2008).CrossRefGoogle Scholar
20.Zhijun, L., Ge, S. S., Adams, M. and Wijesoma, W. S., “Adaptive robust output-feedback motion/force control of electrically driven nonholonomic mobile manipulators,” IEEE Trans. Control Syst. Technol. 16 (6), 1308–1315 (2008).Google Scholar
21.Brackbill, E. A., Ying, M., Agrawal, S. K., Annapragada, M. and Dubey, V. N., “Dynamics and Control of a 4-Dof Wearable Cable-Driven upper Arm Exoskeleton,” IEEE International Conference on, Rob. and Autom., 2009. (2009) pp. 2300–2305.Google Scholar
22.Rahman, M. H., Kiguchi, K., Rahman, M. M. and Sasaki, M., “Robotic Exoskeleton for Rehabilitation and Motion Assist,” First International Conference on Industrial and Information Systems, (2006) pp. 241–246.Google Scholar
23.Zhu, W.-H., Piedboeuf, J.-C. and Gonthier, Y., “A dynamics formulation of general constrained robots,” Multibody Syst. Dyn. 16 (1), 37–54 (2006).CrossRefGoogle Scholar
24.Zhu, W. H. and De Schutter, J., “Experimental verifications of virtual-decomposition-based motion/force control,” IEEE Trans. Robot. Autom. 18 (3), 379–386 (2002).Google Scholar
25.Rahman, M. H., Saad, M., Kenné, J. and Archambault, P. S., “Nonlinear Sliding Mode Control Implementation of an Upper Limb Exoskeleton Robot to Provide Passive Rehabilitation Therapy,” In: Intelligent Robotics and Applications (Su, C.-Y., Rakheja, S. and Liu, H., eds.) (Springer Berlin Heidelberg, 2012) pp. 52–62.Google Scholar
26.Craig, J. J., Introduction to Robotics : Mechanics and Control (Pearson/Prentice Hall, Upper Saddle River, N.J., 2005).Google Scholar
27.Zhu, W. H., Yu-Geng, X., Zhang, Z.-J., Zeungnam, B. and De Schutter, J., “Virtual decomposition based control for generalized high dimensional robotic systems with complicated structure,” IEEE Trans. Robot. Autom. 13 (3), 411–436 (1997).Google Scholar
28.Zhu, W. H., Lamarche, T., Dupuis, E., Jameux, D., Barnard, P. and Guangjun, L., “Precision control of modular robot manipulators: The VDC approach with embedded FPGA,” IEEE Trans. Robot. 29 (5), 1162–1179 (2013).CrossRefGoogle Scholar
29.Zhu, W. H. and De Schutter, J., “Adaptive control of mixed rigid/flexible joint robot manipulators based on virtual decomposition,” IEEE Trans. Robot. Autom. 15 (2), 310–317 (1999).Google Scholar
30.Zhu, W. H. and Lamarche, T., “Modular Robot Manipulators Based on Virtual Decomposition Control,” IEEE International Conference on, Robot. and Autom., (2007) pp. 2235–2240.Google Scholar
31.Brigham and Women's Hospital Rehabilitation Services, (2014). Physical Therapy Standards of Care and Protocols. Available: http://www.brighamandwomens.org/Patients_Visitors/pcs/rehabilitationservices/StandardsofCare.aspx [Accessed 2 Sep. 2014].Google Scholar
32.Ferrer, S. B., Ochoa-Luna, C., Rahman, M. H., Saad, M. and Archambault, P. S., “HELIOS: The human machine interface for MARSE robot,” The 6th International Conference on, Human System Interaction (HSI), (2013) pp. 117–122.Google Scholar
33.Zhu, W. H., “Regressor Matrix and Parameter Vector of an Object” In: Virtual Decomposition Control: Toward Hyper Degrees of Freedom Robots. (Springer, Berlin Heidelberg, 2010) pp. 387–389.Google Scholar